Almost Optimality of the Orthogonal Super Greedy Algorithm for μ-Coherent Dictionaries

被引：3
|
作者：
Shao, Chunfang [1 ]
Chang, Jincai [1 ]
Ye, Peixin [2 ,3 ]
Zhang, Wenhui [2 ,3 ]
Xing, Shuo [2 ,3 ]
机构：
[1] North China Univ Sci & Technol, Coll Sci, Tangshan 063210, Peoples R China
[2] Nankai Univ, Sch Math, Tianjin 300071, Peoples R China
[3] Nankai Univ, LPMC, Tianjin 300071, Peoples R China
来源：
AXIOMS | 2022年 / 11卷 / 05期
基金：
中国国家自然科学基金;
关键词：
orthogonal super greedy algorighm; coherence; best n-term approximation; Lebesgue-type inequality; MATCHING PURSUIT; SPARSE SOLUTION; APPROXIMATION; INEQUALITIES; RECOVERY;
D O I：
10.3390/axioms11050186
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
We study the approximation capability of the orthogonal super greedy algorithm (OSGA) with respect to mu-coherent dictionaries in Hilbert spaces. We establish the Lebesgue-type inequalities for OSGA, which show that the OSGA provides an almost optimal approximation on the first [1/ (18 mu s)] steps. Moreover, we improve the asymptotic constant in the Lebesgue-type inequality of OGA obtained by Livshitz E D.
引用
收藏
页数：17
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